Preemptive scheduling of dependent periodic tasks modeled by synchronous dataflow graphs.
RTNS(2016)
Abstract
Advanced features in modern cars have increased the criticality level of embedded applications in automotive. These applications are generally composed of several communicating functions, for which a deterministic data exchanges is crucial. In the industry, applications are designed with high level models such as Matlab/Simulink. They are implemented on an AUTOSAR platform, where they are scheduled with a fixed-priority based Operating System (OS). However, AUTOSAR OS does not directly provide support for deterministic dataflow implementation. In this paper, we present an approach to implement a deterministic dataflow of dependent periodic tasks on preemptive fixed-priority based uniprocessor. We consider a multi-periodic system consisting in several dependent realtime tasks modeled by a Synchronous Dataflow Graph. We use the scheduling of the graph to make the dependent tasks set independent. This permits to insure a deterministic dataflow without requiring synchronization mechanisms. In addition, it allows to use the existing scheduling policies for independent tasks. We propose several heuristics which find a scheduling solution in 76 percent of cases and provide a fast method to deal with dependencies in multi-periodic systems.
MoreTranslated text
Key words
Syhnchronous DataFlow Graph, graph scheduling, dependent tasks, task scheduling
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined